Local Field Potentials: Myths and Misunderstandings

Abstract

The intracerebral local field potential (LFP) is a measure of brain activity that reflects the highly dynamic flow of information across neural networks. This is a composite signal that receives contributions from multiple neural sources, yet interpreting its nature and significance may be hindered by several confounding factors and technical limitations. By and large, the main factor defining the amplitude of LFPs is the geometry of the current sources, over and above the degree of synchronization or the properties of the media. As such, similar levels of activity may result in potentials that differ in several orders of magnitude in different populations. The geometry of these sources has been experimentally inaccessible until intracerebral high density recordings enabled the co-activating sources to be revealed. Without this information, it has proven difficult to interpret a century's worth of recordings that used temporal cues alone, such as event or spike related potentials and frequency bands. Meanwhile, a collection of biophysically ill-founded concepts have been considered legitimate, which can now be corrected in the light of recent advances. The relationship of LFPs to their sources is often counterintuitive. For instance, most LFP activity is not local but remote, it may be larger further from rather than close to the source, the polarity does not define its excitatory or inhibitory nature, and the amplitude may increase when source's activity is reduced. As technological developments foster the use of LFPs, the time is now ripe to raise awareness of the need to take into account spatial aspects of these signals and of the errors derived from neglecting to do so.

Respiration competes with theta for modulating parietal cortex neurons

“…A common issue in LFP analysis is to infer whether the detected oscillations represent local activity (presumably synaptic) or else passive/return currents due to volume conduction from current dipoles located elsewhere [1,46,47]. Although RR has low amplitude in the parietal cortex, our results support the notion that it does directly and specifically impact the local network, which in turn is likely to contribute to RR appearance at the LFP level.…”

Modulation of local field potentials and neuronal activity in primate hippocampus during saccades

“…We found that fixation and saccadic effects occurred in different frequency ranges. Recent work has cautioned against the a priori labelling and filtering of LFP data, while highlighting the lack of coherence in frequency selections (Einevoll, Kayser, Logothetis, & Panzeri, ; Herreras, ). Indeed, a broad range of frequencies have been arbitrarily identified as “classical” theta, anywhere between 3 and 12 Hz (Colgin, ; Ekstrom & Watrous, ; Jacobs, ; Killian, Jutras, & Buffalo, ; Skaggs et al, ).…”

“…Recent studies have challenged the "local" extent of LFPs (Canolty et al, 2010;Herreras, 2016;Kajikawa & Schroeder, 2011), raising the question of whether the measured correlations with saccade parameters could reflect eye muscle artifacts or signals coming from neighboring structures, such as the thalamus. While the gamma band effect we measured here is likely due to myogenic contamination (Katz et al, 2018;Kovach et al, 2011), we have several reasons to believe that this is not the case for the low-frequency effects.…”

Hippocampal theta bursting and waveform shape reflect CA1 spiking patterns

“…Throughout this research, clear evidence has emerged showing that local spiking probability is coupled to phases of the oscillatory local field (Li et al, 1952) , resulting in theories about how these oscillations may function to aid communication among brain networks (Fries, 2005;Peterson and Voytek, 2018;Roux and Uhlhaas, 2014;Voytek and Knight, 2015) . Though we have a good understanding of how current sources summate and manifest as field potential fluctuations (forward model), interpretations of these oscillations is challenging because many different biological processes can yield the same field potential fluctuation (inverse model) Herreras, 2016;Herreras et al, 2015;Pesaran et al, 2018) .…”

“…There is a general consensus that the prominent contributor to the low frequency component of the field potential (<100 Hz) is synaptic activity (Einevoll et al, 2007(Einevoll et al, , 2013Haider et al, 2016;Mazzoni et al, 2015;Mitzdorf, 1985) , but interpretation remains complicated because the resultant field potential is significantly influenced by anatomical geometry, connectivity, tissue electrical properties, and nonsynaptic ionic currents Herreras, 2016;Lindén et al, 2010Lindén et al, , 2011Ness et al, 2016;Reimann et al, 2013) . Though relatively simple models can capture certain relationships between the field potential and neuronal activity (Gao et al, 2017;Mazzoni et al, 2015;Miller et al, 2009) , the details of the relationship between the two are mostly unknown.…”